Abstract

Background: Few studies have examined geographic disparities in breast cancer mortality at smaller geographical areas in the United States (U.S,) taking into account geographical details and spatial auto-correlations. Though these have identified counties with high breast cancer mortality risk, county-level socioeconomic attributes which are proven to be risk factors for breast cancer mortality were not examined and accounted for. The aim of this study is to efficiently map the spatial variation in the female breast cancer mortality rates across the counties of U.S., and to identify the high risk geographical clusters while adjusting for the county attributes, such as ethnic distribution of the population, educational attainment, poverty, unemployment and health care access.

Methodology: County-specific age standardized rates for breast cancer mortality for women aged ≥ 20 years in the U.S. were obtained for 3,109 counties from Surveillance Epidemiology and End Results (SEER) program from 1990-2012. We gathered county attributes from American Community Survey, such as the percentages of Hispanic white, Non-Hispanic white, Non-Hispanic black, < high school education, below 200% poverty, urban, foreign born, language isolation, women aged ≥ 40 years with mammography within last 2 years, and median household income. Then, we applied factor analysis to condense county attributes into three factors as covariates namely Hispanic immigrants, health care access among urban high income population, and non-Hispanic black unemployment. Spatiotemporal analysis was carried out by the structured additive regression model to incorporate spatial functions and Bayesian inference using Markov Chain Monte Carlo simulation techniques. Deviance Information Criteria was used for model comparisons and selections.

Results: Moran's index for the age standardized breast cancer mortality rate was 0.12 (p-value :< 0.001) suggesting the existence of spatial dependence for the breast cancer mortality among the counties of U.S. Estimated effects [Mean (95%CI)] of spatial estimates for the factors were 0.03(0.02-0.05) for Hispanic immigrant culture, 0.06(0.04-0.09) for health care access among urban & high income groups and 0.41(0.31-0.51) for the non-Hispanic black unemployment. Counties in the Southwest region, Rocky mountain region and those in the western border of Midwest region of U.S with more Hispanic immigrants, have significantly lower mortality rates, a finding that can attributed to the lower incidence of breast cancer among Hispanics. As the mammography screening among urban and high income areas of the counties in the Mid-west region increase, the risk of breast cancer mortality increase significantly above the national average. And as the non-Hispanic black unemployment rates increase, the counties of Mid-West and those of South-West were at higher risk of mortality compared to national average. The percentage of counties with significant positive spatial function were 3.8% for the health care access factor and 6.3% for non-Hispanic black unemployment factor.

Conclusion: These initial results might explain social, cultural, and other reasons for the observed geographic variations, and in turn, could support a stronger theoretical basis for public health policy.